Sensor planning is a general requirement in inspections, measurements, and robot localization, navigation, or mapping relative to an area of interest. Areas of interest may include a component, part, detail, assembly, or spatial area, such as a geographic area or other 2D or 3D space. Additionally, a general requirement of inspection and measurement methods, and autonomous robotics, is to employ sensors to capture samples, such as images or measurements, of the area of interest in sufficient detail and a desired level of completeness.
A known solution for sensor planning is to utilize manually programmed sensor plans, such as coordinate systems, routes, or pathways, for capturing the desired area of interest. However, manually programmed sensor plans often require unchanging and/or substantially certain areas of interest. Therefore, areas of interest that deviate from the preprogrammed plan often result in sampling errors, omissions, or other failures.
Another known solution for sensor planning may include programming a robot to capture large quantities of samples to ensure the area of interest is captured in sufficient detail and a desired level of completeness. However, capturing large quantities of samples is similarly costly, time consuming, and results in inefficient quantities of redundant samples. Additionally, the unknown nominal areas of interest, or changes to the area of interest relative to nominal, may similarly result in errors, omissions, or failures to capture the desired area of interest.
Therefore, there exists a need for robotic sensing systems and methods of sensor planning that may capture samples of the desired and/or potentially unknown or changing area of interest in sufficient detail and completeness while minimizing redundancy and time.